Robotic Drive System Modularity

ABSTRACT

The subject disclosure is directed towards a robot device including a computational intelligence system that can be coupled to/decoupled from different interchangeable mobility mechanisms at different times. The robot may operate with its intelligence portion detached from the mobility portion, whereby the intelligence portion may be easily to interact therewith out lifting the (typically dirty) mobility mechanism. The robot may operate according to a coupled state, a decoupled state, or in a transition state when being moved for purposes of coupling or decoupling.

BACKGROUND

A robot is a complex assembly of sensory awareness, computationalintelligence, and mobility. Sensory and intelligence systems can beeasily designed for broad applications, similar to a computer systemthat can run various applications. Mobility drive systems, however, aretypically highly specialized for specific environments.

To optimize maneuverability and stability, and to present anon-threatening appearance, a home consumer robot typically needs to besmall (approximately toddler-sized). As a result, the stature of a homeconsumer robot is (typically) substantially shorter than a standingadult. When a user wants to interact with such a robot at a moreconvenient level, something closer to eye level, it is desirable for theuser to be able to lift that robot onto a countertop or tabletop.However, a robot's drive system collects dirt and dust, and the robotcan be heavy, making the lifting operation undesirable in manyinstances.

SUMMARY

This Summary is provided to introduce a selection of representativeconcepts in a simplified form that are further described below in theDetailed Description. This Summary is not intended to identify keyfeatures or essential features of the claimed subject matter, nor is itintended to be used in any way that would limit the scope of the claimedsubject matter.

Briefly, various aspects of the subject matter described herein aredirected towards a technology by which a robot device includes acomputational intelligence system that can be coupled to/decoupled fromdifferent interchangeable mobility mechanisms at different times, makingthe intelligence portion of the robot detachable from the mobilityportion. The robot may drive a mobility mechanism when coupled to such amobility mechanism, or operate in a stationary state, including tooutput information to a human via an interface, when decoupled from anymobility mechanism. A sensor set provides one or more signals to thecomputational intelligence system by which the computationalintelligence system detects whether a mobility mechanism is coupled ornot. In one aspect, the sensor set provides signals to detect when therobot is being carried.

In one aspect, the detachable computational intelligence system (e.g.,contained in a lightweight housing) is dimensioned to be lifted up by ahuman of reasonable strength for placing upon an elevated surface. Notonly does the detachability facilitate lifting by reducing the amount ofweight, but also facilitates lifting because the mobility portion, whichis typically dirty, remains on the ground whereby only the computationalintelligence system needs be placed on a table, counter, chair or thelike to raise it closer to eye level.

In one aspect, the robot operates differently depending on its currentstate, e.g., coupled, decoupled or in transition. For example, the robotdevice may disable any controlled movement of its housing, gesture inputmay be disabled, and so forth when in the transition state.

Other advantages may become apparent from the following detaileddescription when taken in conjunction with the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is illustrated by way of example and not limitedin the accompanying figures in which like reference numerals indicatesimilar elements and in which:

FIGS. 1A-1C are block diagrams representing example embodiments of arobotic device in which a computational intelligence system of therobotic device may be coupled and decoupled from a mobility mechanism ofthe robotic device.

FIG. 2 is a representation of a robot device coupled to a wheel-typemobility system.

FIG. 3 is a representation of a robot device decoupled from a wheel-typemobility system.

FIG. 4 is a representation of a robot device coupled to a tread-typemobility system.

FIG. 5 is a representation of a robot device decoupled from any mobilitysystem and placed on a surface where the robot device may continue tooperate in a decoupled state.

FIG. 6 is a representation of a robot device coupled to a tabletopmobility base where the robot device may continue to operate.

FIG. 7 is a state diagram representing example states in which a roboticdevice may operate.

FIG. 8 is a block diagram representing an exemplary non-limitingcomputing system or operating environment in which one or more aspectsof various embodiments described herein can be implemented.

DETAILED DESCRIPTION

Various aspects of the technology described herein are generallydirected towards a robot device that includes a detachable,modular/interchangeable drive mechanism, by which the robot may functionas a static device, or a mobile device that changes its type oflocomotion for movement over various terrains/other purposes as needed.The robot device thus is able to be adapted to different environmentsand change its operating functionality depending on what drive mechanismhardware is attached. Not only does the modularity of the drivemechanism facilitate flexibility and extensibility with respect todifferent types of mobility, but the detachability of the drivemechanism makes the computational intelligence system of the robotremovable, whereby it is physically lighter in weight for lifting andshorter in height, as well as cleaner because only the drive mechanismcontacts the terrain.

It should be understood that any of the examples herein arenon-limiting. For example, various models and the like are used asexamples herein, however other models than those exemplified may beused. As such, the present invention is not limited to any particularembodiments, aspects, concepts, structures, functionalities or examplesdescribed herein. Rather, any of the embodiments, aspects, concepts,structures, functionalities or examples described herein arenon-limiting, and the present invention may be used various ways thatprovide benefits and advantages in robotic technology in general.

FIGS. 1A-1C are block diagrams representing some example alternativeimplementations of a robot device 102A-102C, respectively, configuredfor mobility via an interchangeable/modular mobility (drive) mechanism104. In FIG. 1A, a computational intelligence system 106 couples to(e.g., mounts atop) the mobility mechanism 104. This provides mobilityto the robot device 102 so that the computational intelligence system106 is able to be transported over one or more kinds of terrain, basedupon instructions from the computational intelligence system 106. Notonly is terrain a consideration, but different mobility mechanisms mayaddress other, different mobility needs, such as top speed, precision,durability, weight, long distance, endurance, and so forth, for example.

In general, a sensor set 108 comprising one or more sensors provides thecomputational intelligence system 106 with one or more signals toindicate the robot device's current state. This includes one or moresignals used for detecting when the computational intelligence system106 is coupled to the mobility mechanism 104 and when it is decoupled.The sensor set may include any mechanical, electrical, optical and/ormagnetic sensor or sensors, such as a sensor that detects a latchmechanism that couples/decouples the mobility mechanism. Also, asdescribed below, there are different types of interchangeable modularmobility mechanisms, and then sensor set 108 may providemechanism-specific information whereby the computational intelligencesystem 106 knows which type of mobility mechanism is currently coupledto it.

The computational intelligence system 106 includes a processor 110,memory 112 and interface 114. In the implementation shown in FIG. 1A,the computational intelligence system 106 also includes a device battery116 (or other suitable portable power source).

FIG. 1B is similar to FIG. 1A, and thus is not described again except tonote that the modular mobility mechanism 104B includes its own, separatedrive battery 118. The battery may be pluggable into different modularmobility mechanisms to allow sharing, recharging one while usinganother, and so forth. As will be understood, the computationalintelligence system 106 is designed to be relatively light, and thushaving a separate drive battery 118 in the modular mobility mechanism104B allows the computational intelligence system's battery 116 to beappreciably smaller/lighter. Note that the computational intelligencesystem 106 may draw power from the drive battery 118 when coupled to themobility mechanism 104B, however the computational intelligence system106 remains operational when decoupled, and thus uses the battery 116 atleast as an auxiliary power source when decoupled.

FIG. 1C is another implementation that is generally similar in thecomputational intelligence system 106 and mobility mechanism 104Caspects, however in this implementation, the computational intelligencesystem 106 and mobility mechanism 104C coupled together via anintermediate mechanism 120. In this example, the intermediate mechanismincludes the drive battery 118, whereby different mobility mechanismsare able to share the same drive battery (even if not pluggable) andpossibly other shared components, such as a motor, gears and so forth.Note that at least part of the sensor set 108C is able to detect whenall components 106, 104C and 120 are coupled, and for purposes ofsimplicity the sensor set 108C is shown in the intermediate mechanism,even though the sensor set 108C may only have a conductor or the likeextending through the intermediate mechanism 120 that completes acircuit when all are coupled, for example. Also, at least part of thesensor set includes a motion sensor 122 that detects when thecomputational intelligence system is moving (e.g., vertically), such aswhen transitioning from a coupled state to a decoupled state. One way todo this is by having the motion sensor 122 physically coupled to thecomputational intelligence system 106, as generally represented in FIG.1C; other ways are feasible, however, such as to machine vision processa camera's captured frames to determine such vertical motion. Note that“motion sensor” includes the concept of conventional motion sensors aswell as other sensor types, for example a proximity sensor detectingdistance from the surface (floor or table), an accelerometer, agyroscope and so forth.

FIGS. 2 and 3 represent the detachability of one example embodiment of arobot device 202 with the modular mobility mechanism 104 in awheel-based embodiment 204, and the computational intelligence system106 in a detachable upper housing 206. FIG. 2 shows the coupled state,while FIG. 3 shows the decoupled state. As described below, thecomputational intelligence system 106 remains operational in thedecoupled state.

FIGS. 2 and 4 represent the interchangeable/nodular nature of themobility mechanisms, with the modular mobility mechanism in thewheel-based embodiment 204 of FIG. 2, and in an alternative tread-basedembodiment 404 of FIG. 4. The same computational intelligence system 106in the detachable upper housing 206 may be coupled to either mobilitymechanism 204 or 404, as well as other types of mobility mechanisms(e.g., arranged for climbing stairs or other such terrain). Note furtherthat a different computational intelligence system 106 may be used withthe mobility mechanisms, e.g., one with more computational power, onewith different applications, and so forth.

FIG. 5 represents another desirable aspect of the robot device, namelythat in the decoupled state, the computational intelligence system 106in the detachable upper housing 206 may be placed on an elevated surfacesuch as a table, counter or chair for interaction with a human. Asmentioned above, the robot's size is intended to be non-intimidating,such as the size of a toddler, but is ordinarily no more than three orpossibly four feet in height. The housing 206 with the containedcomputational intelligence system 106 is ordinarily far cleaner than anymobility mechanism, and is also shorter and lighter (e.g., a few poundsat most, ordinarily not more than twenty) without a mobility mechanismcoupled thereto, making lifting into an elevated position more desirableand easy for a human of reasonable strength.

FIG. 6 is a representation of another alternative, namely the housing206/computational intelligence system 106 of the robot being placed in atabletop “mobility” base 604. The tabletop mobility base 604 is analternative base with limited mobility, such as only a rotational axisof mobility, for example (or possibly some vertical movement). Thetabletop mobility base 604 may be placed on a tabletop, countertop, orchair. When placed in the mobility base 604, the computationalintelligence system may rotate to face multiple participants in aconversation, for example, with the base 604 also optionally configuredto provide power and/or charge the battery of the computationalintelligence system 106.

FIG. 7 is a state diagram showing example states of the robot device,namely coupled 770 in which the computational intelligence system 107 iscoupled to a mobility mechanism, decoupled 772 therefrom, or in atransition state 774. Note that these states may correspond to thesensor states indicated in FIG. 7.

The robot device operates differently when in these states. Some exampleoperating differences of one embodiment are described herein; these arenon-limiting examples, may or may not be present in a givenimplementation, and other example operating differences may exist in agiven implementation.

When the robot is lifted vertically and the sensor set also indicatesthe computational intelligence system and mobility mechanism aredecoupled, the robot device is in the transition state 774. In thetransition state 774, robot motion is paused and disabled, includinghead rotation and tilt, projector, drive systems and other. One or moretypes of input/interaction may be disabled, such as gesture and/ortouch-sensitive input, however speech and remote control input continuenormally. Note that one type of remote control input is referred to as“pendant” input, because the user may wear the remote control around theneck in one embodiment of a remote control.

Lifting the robot does not change its mode (e.g., engaged with a person,running in a self-directed operation, and so forth). However, if therobot was performing a task involving motion (which may correspond toself-directed operation), such as performing navigation, head rotation,projector rotation, and so forth, then that motion is suspended and thetask is paused. Applications that are running on the robot mayindividually determine how this task pausing is handled.

If the robot was engaged with a person (or possibly another robot) whenlifted, then an engagement timeout timer is reset. If the engagementtimer expires while the robot is carried, then engagement times out.

The robot retains the capability to continue its non-motion tasks whileit is carried without interruption, except that gesture input issuspended. Applications individually determine how gesture inputsuspension is handled.

When the robot is set down in the decoupled state 772 and is no longerin the transition state 774, motion (other than via a mobility mechanismwhich is non-applicable in the decoupled state) is restored, and gestureinput is enabled. Setting down the robot does not change its mode(engaged, self-directed, and so forth). If the robot was engaged whenset down, then the engagement timeout timer is reset. If the robot wasperforming a task involving motion (navigation, head rotation, projectorrotation, and the like) before lifting and detachment, then the robot iscapable of continuing that task. Applications may individually determinehow resuming a task is handled. The robot remains capable of continuingnon-motion tasks.

When the robot is reattached and enters the coupled state, the robotbehaves the same as in the decoupled (stationary) state 772, but furtherhas mobility. Any mobility-related motion task or tasks may be resumed.Note however that the type of mobility mechanism may have changed,making some tasks no longer possible, e.g., the robot cannot go up ordown stairs if the mobility mechanism is not able to do so, as enforcedby the computational intelligence system and possibly other failsafemechanisms. Thus, the intelligence system is configured to prevent themobility mechanism from transporting the robot device over a terrain forwhich the mobility mechanism is not designed. When such a situation isencountered, applications may individually determine how to handle thissituation subject to the prevented locomotion.

Exemplary Computing Device

As mentioned, advantageously, the techniques described herein can beapplied to any device. It can be understood, therefore, that handheld,portable and other computing devices and computing objects of all kindsare contemplated for use in connection with the various embodiments. Forexample, a general purpose remote computer described below in FIG. 8 isbut one example of a computing device that may form much of the hardwareand underlying software platform for a robot device.

Embodiments can partly be implemented via an operating system, for useby a developer of services for a device or object, and/or includedwithin application software that operates to perform one or morefunctional aspects of the various embodiments described herein. Softwaremay be described in the general context of computer executableinstructions, such as program modules, being executed by one or morecomputers, such as client workstations, servers or other devices. Thoseskilled in the art will appreciate that computer systems have a varietyof configurations and protocols that can be used to communicate data,and thus, no particular configuration or protocol is consideredlimiting.

FIG. 8 thus illustrates an example of a suitable computing systemenvironment 800 in which one or aspects of the embodiments describedherein can be implemented, although as made clear above, the computingsystem environment 800 is only one example of a suitable computingenvironment and is not intended to suggest any limitation as to scope ofuse or functionality. In addition, the computing system environment 800is not intended to be interpreted as having any dependency relating toany one or combination of components illustrated in the exemplarycomputing system environment 800.

With reference to FIG. 8, an exemplary remote device for implementingone or more embodiments includes a general purpose computing device inthe form of a computer 810. Components of computer 810 may include, butare not limited to, a processing unit 820, a system memory 830, and asystem bus 822 that couples various system components including thesystem memory to the processing unit 820.

Computer 810 typically includes a variety of computer readable media andcan be any available media that can be accessed by computer 810. Thesystem memory 830 may include computer storage media in the form ofvolatile and/or nonvolatile memory such as read only memory (ROM) and/orrandom access memory (RAM). By way of example, and not limitation,system memory 830 may also include an operating system, applicationprograms, other program modules, and program data.

A user can enter commands and information into the computer 810 throughinput devices 840. A monitor or other type of display device is alsoconnected to the system bus 822 via an interface, such as outputinterface 850. In addition to a monitor, computers can also includeother peripheral output devices such as speakers and a printer, whichmay be connected through output interface 850.

The computer 810 may operate in a networked or distributed environmentusing logical connections to one or more other remote computers, such asremote computer 870. The remote computer 870 may be a personal computer,a server, a router, a network PC, a peer device or other common networknode, or any other remote media consumption or transmission device, andmay include any or all of the elements described above relative to thecomputer 810. The logical connections depicted in FIG. 8 include anetwork 872, such local area network (LAN) or a wide area network (WAN),but may also include other networks/buses. Such networking environmentsare commonplace in homes, offices, enterprise-wide computer networks,intranets and the Internet.

As mentioned above, while exemplary embodiments have been described inconnection with various computing devices and network architectures, theunderlying concepts may be applied to any network system and anycomputing device or system in which it is desirable to improveefficiency of resource usage.

Also, there are multiple ways to implement the same or similarfunctionality, e.g., an appropriate API, tool kit, driver code,operating system, control, standalone or downloadable software object,etc. which enables applications and services to take advantage of thetechniques provided herein. Thus, embodiments herein are contemplatedfrom the standpoint of an API (or other software object), as well asfrom a software or hardware object that implements one or moreembodiments as described herein. Thus, various embodiments describedherein can have aspects that are wholly in hardware, partly in hardwareand partly in software, as well as in software.

The word “exemplary” is used herein to mean serving as an example,instance, or illustration. For the avoidance of doubt, the subjectmatter disclosed herein is not limited by such examples. In addition,any aspect or design described herein as “exemplary” is not necessarilyto be construed as preferred or advantageous over other aspects ordesigns, nor is it meant to preclude equivalent exemplary structures andtechniques known to those of ordinary skill in the art. Furthermore, tothe extent that the terms “includes,” “has,” “contains,” and othersimilar words are used, for the avoidance of doubt, such terms areintended to be inclusive in a manner similar to the term “comprising” asan open transition word without precluding any additional or otherelements when employed in a claim.

As mentioned, the various techniques described herein may be implementedin connection with hardware or software or, where appropriate, with acombination of both. As used herein, the terms “component,” “module,”“system” and the like are likewise intended to refer to acomputer-related entity, either hardware, a combination of hardware andsoftware, software, or software in execution. For example, a componentmay be, but is not limited to being, a process running on a processor, aprocessor, an object, an executable, a thread of execution, a program,and/or a computer. By way of illustration, both an application runningon computer and the computer can be a component. One or more componentsmay reside within a process and/or thread of execution and a componentmay be localized on one computer and/or distributed between two or morecomputers.

The aforementioned systems have been described with respect tointeraction between several components. It can be appreciated that suchsystems and components can include those components or specifiedsub-components, some of the specified components or sub-components,and/or additional components, and according to various permutations andcombinations of the foregoing. Sub-components can also be implemented ascomponents communicatively coupled to other components rather thanincluded within parent components (hierarchical). Additionally, it canbe noted that one or more components may be combined into a singlecomponent providing aggregate functionality or divided into severalseparate sub-components, and that any one or more middle layers, such asa management layer, may be provided to communicatively couple to suchsub-components in order to provide integrated functionality. Anycomponents described herein may also interact with one or more othercomponents not specifically described herein but generally known bythose of skill in the art.

In view of the exemplary systems described herein, methodologies thatmay be implemented in accordance with the described subject matter canalso be appreciated with reference to the flowcharts of the variousfigures. While for purposes of simplicity of explanation, themethodologies are shown and described as a series of blocks, it is to beunderstood and appreciated that the various embodiments are not limitedby the order of the blocks, as some blocks may occur in different ordersand/or concurrently with other blocks from what is depicted anddescribed herein. Where non-sequential, or branched, flow is illustratedvia flowchart, it can be appreciated that various other branches, flowpaths, and orders of the blocks, may be implemented which achieve thesame or a similar result. Moreover, some illustrated blocks are optionalin implementing the methodologies described hereinafter.

CONCLUSION

While the invention is susceptible to various modifications andalternative constructions, certain illustrated embodiments thereof areshown in the drawings and have been described above in detail. It shouldbe understood, however, that there is no intention to limit theinvention to the specific forms disclosed, but on the contrary, theintention is to cover all modifications, alternative constructions, andequivalents falling within the spirit and scope of the invention.

In addition to the various embodiments described herein, it is to beunderstood that other similar embodiments can be used or modificationsand additions can be made to the described embodiment(s) for performingthe same or equivalent function of the corresponding embodiment(s)without deviating therefrom. Still further, multiple processing chips ormultiple devices can share the performance of one or more functionsdescribed herein, and similarly, storage can be effected across aplurality of devices. Accordingly, the invention is not to be limited toany single embodiment, but rather is to be construed in breadth, spiritand scope in accordance with the appended claims.

1. In a computing environment, a robotic device comprising: a pluralityof interchangeable mobility mechanisms of different types correspondingto different kinds of locomotion or other movement, or both locomotionand other movement, each mobility mechanism configured to be coupled toa computational intelligence system and decoupled from the computationalintelligence system at different times, each mobility mechanismconfigured to support and move the computational intelligence systembased upon instructions from the computational intelligence system; thecomputational intelligence system configured with a processor, a memoryand an interface, the computational intelligence system configured toprovide instructions that drive a mobility mechanism when coupled tothat mobility mechanism, and to operate in a stationary state includingto output information to a human via the interface when decoupled fromany mobility mechanism; and a sensor set coupled to the intelligencesystem to provide one or more signals to the computational intelligencesystem by which the computational intelligence system detects whether amobility mechanism is coupled or not.
 2. The robotic device of claim 1wherein when a mobility mechanism is coupled, the intelligence systemfurther detects based upon the one of more signals which type ofmobility mechanism is attached.
 3. The robotic device of claim 2 whereinthe intelligence system is configured to prevent the mobility mechanismfrom moving the robot device over a terrain for which the mobilitymechanism is not designed.
 4. The robotic device of claim 1 wherein thesensor set comprises a mechanical, electrical, optical or magneticsensor, or any combination of a mechanical, electrical, optical ormagnetic sensor.
 5. The robotic device of claim 1 wherein the sensor setcomprises at least one sensor that provides signals to detect when therobot is being carried.
 6. The robotic device of claim 1 wherein therobotic device is dimensioned to have a non-intimidating height when thecomputational intelligence system is coupled to an interchangeablemobility mechanism, and wherein the computational intelligence system isdimensioned to be lifted up by a human of reasonable strength forplacing upon an elevated surface when decoupled from any interchangeablemobility mechanism.
 7. The robotic device of claim 1 wherein one of themobility mechanisms comprises a mobility base configured to rotate ahousing containing the computational intelligence system.
 8. The roboticdevice of claim 1 wherein the computational intelligence system iscoupled to a first power source, and wherein the mobility mechanism iscoupled to a second power source.
 9. The robotic device of claim 1further comprising an intermediate mechanism, wherein the computationalintelligence system is coupled to the mobility mechanism via theintermediate mechanism.
 10. The robotic device of claim 9 wherein theintermediate mechanism includes a motor that is shared by at least twodifferent mobility mechanisms when coupled at different times to theintermediate mechanism.
 11. In a computing environment, a methodperformed at least in part on at least one processor, comprising:detecting a decoupled state of a robot device, in which the decoupledstate corresponds to a computational intelligence system being decoupledfrom a mobility mechanism; detecting a coupled state of a robot device,in which the coupled state corresponds to a computational intelligencesystem being coupled to a mobility mechanism; detecting a transitionstate of a robot device, in which the transition state corresponds to acomputational intelligence system being decoupled from a mobilitymechanism and being moved by another entity; and operating the robotdevice with at least one difference in the transition state relative toeach other state.
 12. The method of claim 11 wherein in the transitionstate, operating the robot device comprises pausing or disabling, orboth pausing and disabling, robot motion.
 13. The method of claim 11wherein in the transition state, operating the robot device comprisesdisabling at least one type of input.
 14. The method of claim 11 whereinin the transition state, operating the robot device comprises timing outan engagement that was taking place before detecting the transitionstate if the robot device remains in the transition state beyond atimeout time, or resuming an engagement if the robot device exits thetransition state before the timeout time is reached.
 15. The method ofclaim 11 wherein in the coupled state or the decoupled state, operatingthe robot device comprises enabling each type of input that is disabledin the transition state.
 16. The method of claim 11 wherein in thecoupled state, operating the robot device comprises fully enabling robotmotion.
 17. The method of claim 11 wherein in the coupled state,operating the robot device comprises resuming a motion-related task. 18.The method of claim 11 wherein in the decoupled state, operating therobot device comprises enabling robot motion of at least part of ahousing that contains the computational intelligence system.
 19. In acomputing environment, a robotic device comprising, a mobility mechanismand a computational intelligence system, the computational intelligencesystem configured to be coupled to the mobility mechanism and decoupledfrom the mobility mechanism, the computational intelligence systemconfigured to operate in a stationary state when decoupled from themobility mechanism, to operate in a transition state when decoupled fromthe mobility mechanism and being moved, and to operate in a coupledstate in which the mobility mechanism is configured to support and movethe computational intelligence system based upon instructions from thecomputational intelligence system.
 20. The robotic device of claim 19wherein the computational intelligence system is contained in a housingconfigured for controlled movement that is independent of movement ofthe housing caused by driving of the mobility mechanism, and wherein thecontrolled movement is disabled while in the transition state andenabled while in the decoupled state.